1. Field of the Invention
The invention relates generally to modeling and searching data patterns. In particular, the invention relates to methods, computer programs and apparatuses for modeling and searching patterns in a data sequence.
2. Description of the Related Art
Today, various kinds of procedures are used to detect patterns or structures in data. When found, such patterns can be utilized in many ways.
For example, the art of pattern recognition endeavors to classify patterns based either on prior knowledge or on statistical information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations.
Cluster analysis refers to the assignment of a set of observations into subsets called clusters so that observations in the same cluster are similar in some sense. Clustering is a method of unsupervised learning, and a common technique for statistical data analysis used in many fields, including machine learning, data mining, pattern recognition, image analysis and bioinformatics.
Data mining refers to the process of extracting hidden patterns from data. It is commonly used in a range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery.
However, there tends to be various problems associated with the different pattern detection, recognition and analysis procedures of the prior art. For example, prior art procedures often require some sort of prior information or knowledge about the patterns in order to be effective, particularly when lossless compression is required.
Therefore, an object of the present invention is to alleviate the problems described above and to introduce a solution that allows searching patterns in a data sequence effectively and even without any prior knowledge.